Star Refrigeration’s revolutionary AI and data analysis technology sets the stage for the future of refrigeration at the Industrial Refrigeration Network Conference
Dr Lamb, Group Sales and Marketing Director at Star Refrigeration, said, “I’m delighted to have the opportunity to demonstrate the successful results of implementing AI and live-data analysis technology at our customer’s facilities at the IRN Conference. By sharing Star’s methodology and findings, we hope to champion the adoption of technology capable of transforming data into actionable insights to improve the sustainability of business reliant on industrial refrigeration and heat pump equipment”.
Hosted by Bitzer’s Schaufler Academy, the inaugural IRN Conference aims to become a cornerstone for future developments in the field of sustainable refrigeration solutions.
The event will bring together key cold chain stakeholders from various sectors, including end-users, contractors, installers, consultants, planners, OEMs, and academia to foster thought leadership, share innovative ideas, and strengthen industry collaborations.
As part of the conference agenda, Dr Lamb’s presentation entitled ‘How AI and Remote Data Analysis Can Help Improve and Maintain Efficiency of Refrigeration Systems Over Their Operational Life’ will spotlight how advances in remote monitoring and real-time data analysis, when combined with AI, enable accurate predictions and reductions on energy consumption, operational costs and CO2 emissions.
Dr Lamb, said “By combining modern refrigeration system energy efficient controls and technology with AI, we are transitioning the cooling sector away from the traditional ‘rear view mirror’ approach into a new era where refrigeration system issues are not only reported but predicted and solved before they even happen.
“The technology uses intuitive algorithms that continuously analyse, learn and adapt to optimise refrigeration system performance in real-time. Its predictive capability allows it to foresee potential threats -even the ones hiding in- and advice on remedial actions to increase efficiency and reduce CO2 emissions”
Showcasing recent projects where sophisticated AI-led data analysis technology has been deployed to decarbonise and reduce energy consumption, Dr Lamb will share details of the methodologies employed, the actionable insights gained, and the energy and CO2 projections that contributed to energy savings and reduced environmental impact.
The presentation will outline the core sequential steps of the technology’s implementation lifecycle, from the installation of sensors to deriving insights and implementing cost-avoidance measures. Dr Lamb will explain how data gathered from cooling and heating equipment via standalone loggers, APIs, and existing control systems is transformed into a cloud-based digital twin – a virtual simulation that benchmarks ideal system performance against actual data, identifying inefficiencies.
Attendees will also gain an understanding of the operational advantages of online dashboards, which provide operators with a detailed view of system performance, inefficiencies, recommended corrective measures, trends, and estimates of financial and CO2 savings if remedial action is undertaken. The tool delivers a comprehensive overview and enables multi-site data collection, which allows cooling equipment owners to compare data from various facilities and identify specific focus areas for improvement.
Dr. Lamb will conclude by reflecting on the performance outcomes achieved by current users of AI-driven monitoring and performance optimisation technology. Specifically, he will deep dive into how the technology enabled Tesco to save 4 GWh in energy costs and over 835 tonnes of CO2e in 21 months, with a return on investment of under 3 months. Likewise, Asda achieved a reduction of 5 GWh on energy costs and 1,100 tonnes of CO2e over four and a half years across six distributions centres in the UK.
For more information about the IRN Conference and to register, please visit https://trainings-events.bitzer.de/microsite/index.cfm?l=2680&modus=
To learn more about AI and Remote Data Analysis, please visit https://www.star-ref.co.uk/case-studies/tesco-saves-4gwh-of-energy-and-835-tonnes-of-co2/ and https://www.star-ref.co.uk/case-studies/storage-distribution/asda/
Media Contact
Anna Flanagan, Star Refrigeration Ltd, 01416387916, [email protected], www.star-ref.co.uk
SOURCE Star Refrigeration Ltd
